Endoglycan is a CD34-related marker of marginal zone B cells and is upregulated by TLR ligands (94.7)
Bibliographic record
Abstract
Abstract Endoglycan is a CD34-related sialomucin proposed to play a role in selectin-dependent adhesion of leukocytes to vasculature. Here we have investigated the distribution and function of endoglycan by generating a specific monoclonal antibody to an extracellular epitope of the protein. On non-hematopoietic cells, endoglycan is a relatively selective marker of smooth muscle cells of the gut, airway, and vasculature. Surprisingly, endoglycan does not appear to be a marker of vascular endothelia. Within the mature lineages of the hematopoietic system, endoglycan is restricted to a subset of CD4+CD8+ thymocytes and a subset of mature peripheral B cells. In the spleen of naïve mice, the highest levels of endoglycan surface expression is on marginal zone B (MZB) cells with much lower expression on follicular B cells. To further explore the regulation of endoglycan expression we treated splenocytes with a panel of toll-like receptor (TLR) ligands and cytokines. LPS, Pam3CSK4, CpG and IL-1 all enhanced endoglycan surface expression on splenic B cells approximately four-fold within 48 hrs. Interestingly, TLR ligand-dependent upregulation was blocked in the presence of IL-4, IL-5 or TGF-β, suggesting a selective requirement for endoglycan in T cell independent responses. This work was funded by an operating grant from the Heart and Stroke Foundation of Canada. EJF is a recipient of an NSERC post-graduate scholarship.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".